1. Field of the Invention
The present invention relates to image processing, more particularly, to a color processing method for identification of areas within an image corresponding to monetary banknotes.
2. Description of the Prior Art
Automated identification and verification of known currency bills is a practical application when applied to retail and business environments. Electronic verification of known bill types helps to increase security in monetary transactions, and also prevents vendors from receiving counterfeited currencies. Currency detectors available today typically scan an image of a sample currency, from which a series of tests is performed in order to determine the validity of the sample. The tests used can include the identification of known currency sections or landmarks, holograms, reflective areas, printing patterns, or texture patterns.
However, with advancements and availability of printing technologies, the occurrence of counterfeit, or illegally copied currency has increased. Counterfeiters nowadays have access to sophisticated equipment and methods to duplicate known currencies that are virtually indistinguishable to the human eye and touch.
In addition to the increasing difficulties in identifying legitimate currency bills, is the desire to scan sample currencies from images that are larger than the sample currency being scanned. Doing this will allow a bill (or multiple bills) to be scanned with any common scanner, while possibly allowing the scanning and identification of multiple bills at once. However, doing this introduces more problems as the bills may be presented on arbitrary backgrounds, and may have variations in shift and rotation. Many currency detectors today generally only scan one bill at a time, and only scan the immediate area of the bill in order to omit the need to consider the background, rotation, and alignment of the bill.
Additionally, if the note is scanned while embedded with a complicated image background, it may be very difficult to distinguish the actual note from the image background. The image background may also provide additional noise and/or patterns to complicate the detection process and introduce irregularities and errors.
It is needless to say that without the proper identification of a currency note from its image background, while having various offsets and rotations, optimal conditions for accurate counterfeit currency detection cannot be met.